cnossos-eu sensitivity to meteorological and to some...

CNOSSOS-EU Sensitivity to Meteorological and to Some Road Initial ValueChanges

Panu Maijala1, Jarno Kokkonen2, Olli Kontkanen3

1VTT Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT, Finland.2 3Sito Oy, Department of Environmental Studies and Engineering, Espoo, Finland.

ABSTRACTDuring the implementation process of the CNOSSOS-EU, many questions have been arisen. There are in-consistencies in the guidance, but the most of the questions are related to the acquisition of the initial valuesand their validity. We evaluated the sensitivities of the noise propagation part and the road noise sound powerlevels to the changes of some initial values within their validated ranges. The evaluated parameters werethe probability of occurrence of downward-refraction conditions and the coefficients for the road surface andpropulsion noise. Measured weather values were calculated using three approaches and compared to eachother and to the default values. The results shows that the use of the default weather values increase theimmission levels and thus the number of exposed people. The default rolling and propulsion noise factors ofthe CNOSSOS-EU method are not usable in northern conditions and the national factors should be exploited.

Keywords: CNOSSOS-EU, environmental noise, mapping, rolling and propulsion noise coefficients, weathereffects to noise, favourable conditions, initial values

1. INTRODUCTION

In 2015, an update to the Environmental Noise Directive (END) [1] Annex II was published. According to thenew Annex II [2], all the EU Member States (MS) are required to use Common NOise aSSessment methOdSin the EU (CNOSSOS-EU) from 31 December 2018 onwards.

Some of the MS have already started the implementation of the CNOSSOS-EU framework and foundthat there are still many issues to be resolved in order to complete the process successfully. These issuesinclude derivation of some initial data such as the probability of occurrence of favourable conditions frommeteorological data and determination of the alpha and beta coefficients for road pavements. The EuropeanCommission Directorate-General for Environment is currently working on a corrigendum to address the mostobvious inconsistencies, such as the conflicting frequency bands of interest, found in the Annex II [2].

In Finland, a project was started to prepare the implementation of the CNOSSOS-EU. The members ofthe project are authorities from the Ministry of the Environment, the Finnish transport agency, the Centres forEconomic Development, Transport and the Environment (ELY Centres, responsible for the regional imple-mentation and development tasks of the central government), a consultant company, and a research centre.

The objectives of the Finnish project included preparation of national guidelines for the CNOSSOS-EUand evaluation of the method whether it is mature enough for adoption as a national method. Since themid-1990s, Finland was part of the development team of the Nordic method, Nord2000 [3], representing thebest knowledge of its time. Based on the work for the Nord2000, extensive initial value databases exist formodelling environmental noise. Because CNOSSOS-EU treats the initial values otherwise, new proceduresto handle the national data had to be developed. A combination of a great number of initial values and acomplex calculation method gives also reason to think about how much the whole process allows MS to usetheir own procedures to handle initial data without any significant change in the final result.

[email protected]@[email protected]

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Meteorological data in the CNOSSOS-EU is taken into account by carrying out the calculation of soundlevels in favourable conditions and in homogenous conditions. Long-term level LLT is calculated [4, p. 18]as a sum of levels in favourable conditions LF and homogenous conditions LH weighted by the probabilityof occurrence of favourable conditions (1):

LLT = 10 lg(pf10

LF /10 + (1− pf )10LH/10

), (1)

where pf is the probability of occurrence of downward-refraction conditions in the long term. The pf valuesare expressed in percentages for day (7:00-19:00), evening (19:00-22:00), and night (22:00-7:00) periods.Typically, the pf values are determined to 18 source-receiver directions (20◦ sectors).

Currently, no guidance is given by the European Commission for determination of the pf values. Atpresent, the only known pre-defined values of the probability of occurence exist for 41 locations acrossMetropolitan France [4].

In the CNOSSOS-EU requirements it is mentioned that variation in the input parameters of the emissionpart should have less than 2 dB effect on the calculation results [5]. Using wrong sound power levels asinitial data may lead to significant systematic errors in the calculation results and to avoid this, the essentialvalues of the CNOSSOS-EU should be mitigated to the national conditions and values. When consideringrolling and propulsion noise, a national surface correction may not be enough, rather than the correction forthe A and B factors should be utilised also. In the Nordic countries the current road noise calculation methodis Road Traffic Noise — Nordic Prediction Method (RTN96) [6]. The RTN96 values are over 20 years oldand too ”simple” for the CNOSSOS-EU road model. Much more detailed and fresh measurements are madefor the Nord2000 model [7] and those values can easily be transferred to CNOSSOS. In the CNOSSOS-EUframework, the vehicles are grouped into five separate categories:

• Category 1: Light motor vehicles (passenger cars, delivery vans ⩽ 3.5 tons).

• Category 2: Medium heavy vehicles (medium heavy vehicles, delivery vans > 3.5 tons, buses, etc.with two axles and twin tyre mounting on rear axle).

• Category 3: Heavy vehicles (heavy duty vehicles, touring cars, buses, with three or more axles).

• Category 4: Powered two-wheelers (mopeds, motorcycles).

• Category 5: Open category (future needs).

For total sound power level categories 1–3 are most important and same categories are also used in theNord2000 model. In the Nordic prediction method (RTN96) there are only two categories: light and heavy.For the light, medium, and heavy motor vehicles (categories 1, 2, and 3), the total sound power corresponds tothe energetic sum of the rolling and the propulsion noise. Total sound power level of the source lines m =1,2, or 3 is defined in (2) [2, Eq. 2.2.2]:

LW,i,m(vm) = 10 · lg(10LWR,i,m(vm)/10 + 10LWP,i,m(vm)/10) (2)

The rolling noise sound power level for each octave frequency band i for a vehicle of class m = 1, 2, or3 is defined in (3) and (4) [2, Eq. 2.2.4]:

LWR,i,m = AR,i,m +BR,i,m · lg vmvref

+∆LWR,i,m(vm) (3)

∆LWR,i,m = ∆LWR,road,i,m +∆Lstuddedtyres,i,m +∆LWR,acc,i,m +∆LW,temp (4)

The Coefficients AR,i,m and BR,i,m are given in octave bands (125–4000 Hz) for each vehicle category andfor a reference speed vref = 70 km/h ∆LWR,road,i,m is correction for the effect on rolling noise of a roadsurface with acoustic properties different from the virtual reference surface. This road surface correctionfactor is given by [2, Eq.2.2.19]:

∆LWR,road,i,m = αi,m + βm · lg vmvref

(5)

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The propulsion noise emission includes engine, exhaust, gears, air intake, etc. The propulsion noise soundpower level in the each octave frequency band i for a vehicle of class m is defined as [2, Eq.2.2.11]:

LWP,i,m = AP,i,m +BP,i,m · (vm − vref)

vref+∆LWP,i,m (6)

The coefficients AP,i,m and BP,i,m are given in octave bands for each vehicle category and for a referencespeed vref = 70 km/h.

The assessment of people exposed to noise is based on receivers defined in front of the building façades.Inhabitants of a building are linked to noise level of façade calculation points and the number of inhabitantsis weighted by the length of the represented façade. The most exposed façade noise level is used only inbuildings with a single dwelling per floor level. [2] [5].

In this paper, the sensitivity of the CNOSSOS-EU to some meteorological initial value changes wasevaluated in a case study from Helsinki region. The default weather values of a commercial CNOSSOS-EUsoftware implementation were compared to the measured values in three cases. The hypothesis was thatusing the default weather values the immission levels increase, and thus the number of exposed people. TheCNOSSOS-EU road noise sound power levels were compared to the current Nordic model (RTN96) [6] andthe latest Nord2000 model levels [7]. Correction suggestions for the CNOSSOS-EU road noise sound powercoefficient are presented. During spring 2016 a new road noise emission report form Technical ResearchInstitute of Sweden (SP) will be published. If the sound power level changes are notable, then the new valueswill be exploited.

2. METHODS

2.1 Evaluation of the meteorological data

The pf values were determined with two modeling approaches from three different types of data sets. Sta-tistical weights were calculated for favourable conditions by using local meteorological data. The statisticalweights of favourable conditions describe the frequency of occurrence of downward-refraction conditions.

The meteorological data was provided by the Finnish Meteorological Institute. The three obtained datasets were: a) Helsinki Airport and Helsinki Kaisaniemi (years 2005-2006), b) Espoo Kivenlahti (2006-2013),and c) Espoo Tapiola (2005-2006). There were weather station data including air temperature at height of 2 m,wind direction and velocity at 10, 16 and 31 metre level, and cloudiness in both a) and c) data. The c) dataincluded also computational meteorological data: Klug-Manier stability classes and both the temperature andwind speed gradient data. Because the wind velocity data from the 10 metre level was missing from EspooKivenlahti data and the profile-fitting trials didn’t give any plausible results, we decided to discard that data.

Wind roses were calculated to describe the meteorological conditions in the Helsinki region. Wind veloc-ity gains the maximum values in the south-west direction (225◦, see Figures 1 and 2). This phenomenon isreflected also to the pf values, having higher values between the south and west (180◦ – 270◦).

(a) Height 16 m. (b) Height 10 m, z0=0.5. (c) Height 10 m, z0=0.1.

Figure 1. Wind roses for the data from the meteorological tower in Helsinki Airport. Calm winds 1.45%.

All the meteorological data included also date, time at one hour interval, and geographical position ofthe weather station. All the data was validated, and only the valid data was used for deriving the occurrence

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(a) Height 31 m. (b) Height 10 m, z0=0.5. (c) Height 10 m, z0=0.1.

Figure 2. Wind roses for the data from the meteorological tower in Helsinki Kaisaniemi. Calm winds 0.32%.

values. Weather stations have a very good coverage through Finland; hence the weather station data shouldbe preferred in deriving the local pf values for the use of national noise calculations required by END.

Modeling approach 1: Stability classes

The first method to calculate pf values uses weather station data. The required values are: temperature,wind direction and velocity, cloudiness, and declination of the sun (derived from time and date). Method isdescribed in Harmonoise WP3 [8][9][10]. The meteorological conditions are divided into stability classesand furthermore in 25 classes with different sound speed profiles. The 25 classes was reduced to favourableconditions and to homogenous conditions. This simplification method was derived from the method describedby Plovsing in [11, p. 12], the number of meteo-classes was reduced to four classes: unfavourable, neutral,favourable, and very favourable. A Matlab program developed by Delta was modified and used to calculatethe pf values.

Modeling approach 2: Temperature gradient and wind velocity gradient

The second method is based on the temperature gradient and the wind velocity gradient. Both the wind andtemperature data from two heights is needed, preferably from 2 metres and 10 metres levels. The gradientswere analysed and pf values were derived with method described in the reference literature [4, p. 18]. AMatlab program was used to calculate pf values.

Noise calculations and the number of people exposed to noise

The effect of pf values were evaluated along with the number of people exposed to noise and also by lookingafter differences in noise levels in grid calculations. The noise calculations were done in the test area inHelsinki region on an urban area of 34 km2, where lives 80200 residents, from which 50% live in smallresidential buildings or row houses, 49% in high-rise buildings, and 1% in non-residential buildings. Roadtraffic noise was calculated using a preliminary implementation of the CNOSSOS-EU model in commercialnoise calculation software. Lde and Ln , the day and evening noise level and the night noise level indicators,were used with a calculation height of 2 metres above the ground. Two different approaches were used forthe assessment of people exposed to noise: 1) all inhabitants of a building are linked to noise level of themost exposed façade 2) residents are distributed to all calculation points on the façades and are weighted bythe length of the represented façade.

2.2 Evaluation of the road data

The CNOSSOS-EU sound power levels were calculated along the guidance given in the new Annex II andusing the basic values (e.g. without acceleration, without studded tyres, etc.) [2]. The basic values ofthe current Nord2000 model [7] are given in third octave bands and for the sound power level calculationthe values were converted to octave bands. The calculated A-factors in octave bands are the energy sum ofcorresponding third octave bands and the calculated B-factors are the average from corresponding third octave

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bands. The RTN96 light and heavy vehicles sound power levels were calculated from the sound exposurelevels LAE,10 m using (7)

LWA = LAE + 10 lg(2 · r · vm), (7)

where r = 10 m and vm is expressed in m/s.

The correction for the reference surface condition was calculated according the Nord2000 and the Har-monoise surface correction [7, Eq. 2.3] [12, Table 6.9]:

∆LRoad = RS + 0.25(CS − 11) dB, (8)

where RS= +0.3 dB for the SMA surface and CS is the maximum chip size in mm (8–16 mm).

3. RESULTS

3.1 Case studies — weather in Helsinki region

The calculated pf values for the meteorological data sets described in Section 2.1 are presented in the Ta-bles 1, 2, and 3. The derived pf values differ significantly from the default values: day 50%, evening 75%,and night 100%.

Table 1. Values of pf , Helsinki Kaisaniemi weather station, Harmonoise WP3 methodDirection, ◦ 20 40 60 80 100 120 140 160 180pf,day, % 25 25 23 23 25 25 29 35 39pf,evening, % 29 31 28 27 28 29 31 35 41pf,night, % 41 39 35 33 34 35 36 42 46Direction, ◦ 200 220 240 260 280 300 320 340 360pf,day, % 40 42 43 43 41 34 29 27 25pf,evening, % 44 46 47 49 49 43 36 34 30pf,night, % 51 55 58 60 61 56 51 49 44

Table 2. Values of pf , Helsinki Airport weather station, Harmonoise WP3 methodDirection, ◦ 20 40 60 80 100 120 140 160 180pf,day, % 27 27 27 27 29 35 41 46 48pf,evening, % 31 30 31 32 33 39 45 51 53pf,night, % 41 39 38 38 38 41 46 49 52Direction, ◦ 200 220 240 260 280 300 320 340 360pf,day, % 47 47 47 45 40 34 30 30 29pf,evening, % 53 54 54 53 48 41 34 33 32pf,night, % 54 58 59 59 56 51 46 46 44

Table 3. Values of pf , Espoo weather model, NMPB2008 method.Direction, ◦ 20 40 60 80 100 120 140 160 180pf,day, % 29 29 29 30 30 32 36 44 49pf,evening, % 30 31 32 32 33 36 42 51 56pf,night, % 33 35 37 40 43 45 48 54 58Direction, ◦ 200 220 240 260 280 300 320 340 360pf,day, % 52 53 51 50 48 43 35 30 28pf,evening, % 58 59 58 56 52 44 37 33 31pf,night, % 58 56 54 49 45 38 34 33 33

At largest, the differences in the calculated pf values are −27, −48, and −67 percentages smaller than thedefault values at day, evening, and night periods, respectively. When the Espoo weather model based, more

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accurate pf values, are compared to pf values based on weather station data (see Tables 4 and 5) it seems thatHelsinki Airport pf values are closer to the accurate data than Helsinki Kaisaniemi pf values. Kaisaniemi pfvalues were also calculated with the wind speed that was converted to the height of 10 metres (original datawas from 31 metres). Conversion is based on a constant value of the roughness length z0. The conversionwas made with three z0 values (0.025, 0.1, and 0.5). [10, Eq. 11]

The differences in pf values are about 0%, when z0 = 0.025, between −3% and +1% when z0 = 0.1,and between −14% and +6% when z0 = 0.5. There is a comment in the Delta’s Matlab script, which saysthat the calculation method is valid for a roughness length z0 = 0.025 m.

Table 4. Difference between the pf values in Kaisaniemi and EspooDirection, ◦ 20 40 60 80 100 120 140 160 180pf,day, % -4 -4 -6 -7 -5 -7 -7 -9 -10pf,evening, % -1 0 -4 -5 -5 -7 -11 -16 -15pf,night, % 8 4 -2 -7 -9 -10 -12 -12 -12Direction, ◦ 200 220 240 260 280 300 320 340 360pf,day, % -12 -11 -8 -7 -7 -9 -6 -3 -3pf,evening, % -14 -13 -11 -7 -3 -1 -1 1 -1pf,night, % -7 -1 4 11 16 18 17 16 11

Table 5. Difference between the pf values in Airport and EspooDirection, ◦ 20 40 60 80 100 120 140 160 180pf,day, % -2 -2 -2 -3 -1 3 5 2 -1pf,evening, % 1 -1 -1 0 0 3 3 0 -3pf,night, % 8 4 1 -2 -5 -4 -2 -5 -6Direction, ◦ 200 220 240 260 280 300 320 340 360pf,day, % -5 -6 -4 -5 -8 -9 -5 0 1pf,evening, % -5 -5 -4 -3 -4 -3 -3 0 1pf,night, % -4 2 5 10 11 13 12 13 11

To evaluate the sensitivity of the CNOSSOS-EU sound propagation model to the changes of meteorolog-ical conditions, noise calculations were performed in the Helsinki region on an urban area. The evaluatedparameters were the values of probability of occurrence of downward-refraction conditions. Default pf val-ues, day 50%, evening 75%, and night 100%, were used towards each direction, and compared to the valuesderived from the measured data in three cases. The effect of pf values was evaluated by the number of peopleexposed to noise.

The values of the number of people exposed to noise are shown in the Tables 6, 7, 8, and 9. The resultsshow, that using the default weather values for the day–evening time, the number of exposed people becomesfrom 10% to 20% higher than compared to the to the pf values derived from the measured data. At the nighttime the number of exposed people becomes 60% – 90% higher than compared to pf values derived fromthe measured data. Thus, the use of default values increase the immission levels, and, the number of exposedpeople. There were no significant differences between number of people exposed when the measurements-based pf values were used.

In Finland, the exposure assessment method has been used where inhabitants are linked to the most ex-posed façade. The new CNOSSOS-EU guideline says that the inhabitants have to be allocated to all façadecalculation points [2, Sec. 2.8.]. The definition of the exposed people has a significant effect on the totalnumber of the people exposed to noise. The effect of different exposure assessment methods results in dif-ference of −70% in the number of people exposed to noise. In a recent master’s thesis similar results wereobtained with the percentages between −50% and −70% in the number of people exposed to noise [13].

In the Figures 3 and 4 the differences between the results of the grid calculations with two different pfvalues (Airport minus Default) is visualised. The results of the grid calculations show, that at a close distance(between 50–100 metres), there is only a −1. . . 0 dB difference between the default and measurements-basedweather values. The difference becomes −2. . .−1 dB at longer (over 100 metres) distances at the day time(see Figure 3). At the night time, the difference between the calculated and the default pf values variesbetween −4 and −2 dB at distances over 100 metres (see Figure 4). In this Helsinki region case the pf values

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have effect only on the main roads, where over 55 dB noise levels are reached up to distances of 300–400metres (see Figure 5). At low traffic count streets, with narrow noise zones, there is no effect in the numberof people exposed to noise.

Table 6. The number of people exposed to noise LAeq,day-evening, method: the most exposed façadeWeather data,Calculation method

50–55 dB 55–60 dB 60–65 dB 65– dB sum ofover 55 dB

Kaisaniemi weather station,Harmonoise WP3

16385 8085 2113 2 10200

Airport weather station,Harmonoise WP3

16922 8295 2144 2 10400

Espoo weather model,NMPB2008

17301 8440 2182 4 10600

Default values,(day 50%, evening 75%)

19095 9276 2535 4 11800

Table 7. The number of people exposed to noise LAeq,night, method: the most exposed façadeWeather data,Calculation method



4534 657 2 0 5200


4535 671 2 0 5200


4399 666 2 0 5100

Default values,(night 100%)

6856 1283 2 0 8100

Table 8. The number of people exposed to noise LAeq,day-evening, method: all façade calculation pointsWeather data,Calculation method



8017 2724 426 1 3200


8499 2837 439 1 3300


8727 2910 448 1 3400


9985 3274 500 1 3800

Table 9. The number of people exposed to noise LAeq,night, method: all façade calculation pointsWeather data,Calculation method



1281 122 1 0 1400


1305 125 1 0 1400


1245 120 1 0 1400


2341 255 1 0 2600

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Figure 3: Difference of noise levels between two different calculations and pf values: Airport – default. Day time.

Figure 4: Difference of noise levels between two different calculations and pf values: Airport – default. Nighttime.

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Figure 5: Buildings that are exposed to over 55 dB noise when default pf values are used. Color coded differenceof noise level at most exposed facade with calculated and default pf values. Red buildings: difference below 1 dB.Blue buildings: difference over 1 dB.

Figure 6. CNOSSOS, Nord2000, and RTN96 light vehicle LWA.

Table 10. Rolling noise, Nord2000 light vehicle (cat1) – CNOSSOS-EU light vehicle (cat1)Speed, km/h

Frequency, Hz 40 50 60 70 80 90 100 110 12063 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0125 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3250 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.4500 2.1 2.4 2.5 2.7 2.8 2.9 3.1 3.2 3.21000 0.6 1.1 1.5 1.8 2.1 2.3 2.5 2.7 2.92000 -0.7 -0.4 -0.1 0.2 0.4 0.6 0.7 0.9 1.04000 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.38000 2.8 2.9 2.9 3.0 3.0 3.1 3.1 3.1 3.1∆LWA 0.7 1.0 1.2 1.4 1.6 1.8 1.9 2.0 2.2

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3.2 The Nordic road parameters

One of the main questions was, if it is enough to use a national surface correction ∆LWR,road,i,m (5), orshould there also be national coefficients for the A and B factors, (3) and (6), for the rolling and propulsionnoise parts? Nordic road surfaces are much rougher compared to the middle Europe, because of the winterconditions and the use of studded tires. In the Nordic models, the rolling noise increase in a steeper angle asa function of speed, and the overall level is much higher than in the CNOSSOS-EU (see the Table 10 and theFigure 6). In the Table 10 it is shown that the rolling noise speed coefficient β (5) differences depend on thefrequency band. The propulsion noise of light vehicles is practically meaningless at speeds over 50 km/h. At30 km/h it is at about the same level with the rolling noise. So, for the light vehicles, it would be accurateenough to add a national surface correction, that also could adjust the AR,i,m and BR,i,m factors. The surfacecorrection speed-dependent β factor is the same for all frequency bands, so there will be some error if AR,i,m

and BR,i,m factors are corrected with the surface correction. This error can be minimized, if the β factor isaveraged with the most important frequency range (500 Hz – 2 kHz) and the surface correction β factor isdefined. The calculated surface correction, correcting also the AR,i,m and BR,i,m factors, is presented in theTable 11. Below the correction, a minor error is shown.

Table 11. Surface correction for Nordic reference surface and error after surface correctionαm αm αm αm αm αm αm αm β

63 Hz 125 Hz 250 Hz 500 Hz 1 kHz 2 kHz 4 kHz 8 kHzSMA 0/11 0.0 0.3 0.5 2.7 1.8 0.2 0.1 3 3.6

Speed, km/hFrequency, Hz 40 50 60 70 80 90 100 110 12063 -0.8 -0.5 -0.2 0.0 0.2 0.4 0.6 0.7 0.9125 -0.9 -0.5 -0.2 0.0 0.2 0.4 0.6 0.7 0.8250 -0.9 -0.6 -0.3 0.0 0.2 0.4 0.6 0.8 0.9500 -0.3 -0.2 -0.1 0.0 0.1 0.1 0.2 0.2 0.31000 0.3 0.2 0.1 0.0 -0.1 -0.1 -0.2 -0.2 -0.32000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.04000 -0.7 -0.4 -0.2 0.0 0.2 0.3 0.5 0.6 0.78000 -0.7 -0.4 -0.2 0.0 0.2 0.3 0.5 0.6 0.7

Figure 7. CNOSSOS, Nord2000, and RTN96 heavy vehicles LWA.

The propulsion noise is important for the whole speed range with the vehicle categories 2 and 3. So, ifthe national values vary remarkable, then it is practically mandatory to use the national AP,i,m and BP,i,m

coefficient for the propulsion noise. The sound power levels of the Nordic and the CNOSSOS-EU heavyvehicles are shown in the Figure 7. The category 2 in the Figure 7 and the Table 12 show that at Nordiccountries the heavy vehicles have much higher propulsion sound power levels. Also, the higher rolling noiseemission has a significant effect on the total sound power level (2) at higher speed levels. The reference roadsurface is not very common in the Nordic countries, so that’s why 1.55 dB higher levels are presented withthe SMA 0/16 surface (8).

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Table 12. Propulsion noise medium heavy vehicle (cat2) Nord2000 - CNOSSOSSpeed, km/h

Frequency, Hz 40 50 60 70 80 9063 3.6 3.9 4.1 4.4 4.6 4.9125 6.5 5.7 5 4.2 3.6 3250 6.6 6.4 6.2 6 5.9 5.7500 3.5 4 4.5 4.8 5.1 5.41000 0.8 2.1 3.3 4.2 4.9 5.62000 0.8 1.9 2.9 3.7 4.5 5.24000 1.7 2.5 3.3 3.9 4.5 5.18000 4.4 4.6 4.7 4.8 4.9 4.9∆LWA 1.7 2.3 2.9 3.5 4 4.6

4. SUMMARY

The implementation process of the CNOSSOS-EU framework requires a lot of work at the national level. Theguidance given in the new Annex II of the Environmental Noise Directive contains a number of deficiencies,and it is not fully consistent.

Some of the Member States, including Finland, have already started the implementation process. In Fin-land and the other Nordic countries the some existing national data differs significantly from the CNOSSOS-EU default values and one of the first major tasks will be acquisition of new, reorganising some old, anddeveloping the routines to convert the data to meet the needs of CNOSSOS-EU initial data. These routinesinclude the meteorological and road data, for which CNOSSOS-EU sensitivity was evaluated.

It was shown in this paper, that giving the Member States a freedom to develop their own methods toacquire and derive the initial values, a significant risk of variation to the final results will emerge.

4.1 Conclusions

The main findings of this study are the following:

• The use of the default weather values increase the immission levels and thus the number of exposedpeople.

• The exposure assessment method has a significant effect on the total number of the people exposed tonoise.

• The pf values derived from a simple weather station data represent well the more accurate pf val-ues based on weather model data. It is possible to achieve adequate occurrence values with simplemeteorological data.

• Only minor deviations to pf values were found, when considering the roughness length. Roughnesslength can be utilised in generation of the pf values.

• Local A and B coefficients has to be used for the propulsion and rolling noise in the Nordic countries.Existing Nord2000 data is usable for this purpose.

In this article, we presented the effects of two methods on exposure assessment: 1) inhabitants linked to themost exposed façade method, and 2) inhabitants allocated to all façade calculation points method. The effectof different exposure assessment methods results in difference of −70% in the number of people exposedto noise. Meteorological data from local weather stations should be used to derive the local pf values forthe use of national noise calculations. It is not recommended to use default weather values in Finland. Asa limitation, pf values are valid only for certain environments that meet the assumptions required by themicrometeorological models used to establish these values. For example, these weather values cannot beused for the street canyons in an urban environment. For such an urban environment it is recommended touse the maximum of pf values for each period and direction.

In the Nordic countries, the national road noise emission data significantly differs from the CNOSSOS-EUmodel default values, and the national factors for the rolling and the propulsion noise sound power coefficients

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A and B have to be used. The Nordic A and B coefficients for the rolling and propulsion noise are based onthe measurements in Sweden and Finland, and are already implemented in the Nord2000. Also, the Nord2000road surface correction can be converted to CNOSSSOS-EU. If the commercial software implementation ofthe CNOSSOS-EU doesn’t allow to adding the coefficients for the basic sound power levels, then one optionis to add the rolling noise coefficients to the national surface correction. The drawback is that the error of thesound power levels of heavy vehicles won’t be fixed properly.

REFERENCES

[1] Directive, EN. Directive 2002/49/EC of the European Parliament and of the Council of 25 June 2002Relating to the Assessment and Management of Environmental Noise, June 2002.

[2] Directive, EN. Commission Directive (EU) 2015/996 of 19 May 2015 Establishing Common NoiseAssessment Methods According to Directive 2002/49/EC of the European Parliament and of the Council,May 2015.

[3] Jørgen Kragh, Birger Plovsing, S. Storeheier, and Hans Jonasson. Nordic Environmental Noise Predic-tion Methods, Nord2000. Technical Report AV1719/01, Delta Acoustics & Electronics, March 2001.

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